Edit model card

literary analysis with t5-base

  • t5 sort-of learning to do literary analysis. It was trained on the booksum dataset with chapter (original text) as input and summary_analysis as the output text, where summary_analysis is the sparknotes/cliff notes/etc analysis
  • It was trained for 8 epochs
  • Testing may need to be completed in Colab as it seems to be CPU-intensive. A link to an example notebook is here

Example

!pip install -U -q transformers
!pip install -U -q sentencepiece

from transformers import pipeline

analyzer = pipeline("text2text-generation", 
                    "pszemraj/t5_1_1-base-writing-analysis")
  • enter text and compute.
text = "text to be analyzed goes here"

result = analyzer(
                    text,
                    max_length=int(len(text) * 1.2),
                    no_repeat_ngram_size= 2,
                    repetition_penalty= 2.4,
                    num_beams=4,
                    early_stopping= True,
                )

sample results

  • inputs:

Beren now, he never thought he was going to get that silmaril from the iron crown in thangorodrim, and yet he did, and that was a worse place and a blacker danger than ours. but that’s a long tale, of course, and goes on past the happiness and into grief and beyond it – and the silmaril went on and came to eärendil. and why, sir, I never thought of that before! we’ve got – you’ve got some of the light of it in that star glass that the lady gave you! why, to think of it, we’re in the same tale still! it’s going on. don’t the great tales never end?

  • output:

The silmaril comes to eärendil. it is a long tale, and it is going on beyond the happy ending of the story. in this way, we see that Berens dream has come true. he is in love with her, but she doesnt know how to do it. she thinks about it as if he had never thought of it before. then again, there is an ironic contrast between his dreams and reality. this is not surprising because they are so far apart from each other. they have been together foreshadowing one another. and yet, even though, they were at the same time. but now, their relationship is more important than any other characters. for example, the two men seem to be separated by them. their friendship is very much more interesting. we can imagine what happens when they get back home. when they meet up in the next chapter, however, then, the darkest danger seems to suggest that they will go on the night. now, after all, everyone else does not want to find outwardly.

* NOTE: As the above were not saved in real-time, both the input and output had humanize string formatting applied to quickly clean them as they were copied and pasted from a Colab notebook.

Downloads last month
17
Safetensors
Model size
248M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train pszemraj/t5_1_1-base-writing-analysis